I have configured celery to be deployed in heroku, all Is working well, in fact in my logs at heroku celery is ready to handle the taks. Unfortunately celery doesn't pick my tasks I feel there is some disconnection, can I get some help?
If celery isn't picking up task that means that nothing is talking to its broker. Make sure that the task producer is talking to the same broker url as the celery worker (the broker url will appear in the first 10-15 lines of the celery logs).
Related
We are using celery 3.1.17 with redis backend in our flask 0.10.1 application. On our server every celery task created from some celery task is getting created twice. For example,
#celery.task(name='send_some_xyz_users_alerts')
def send_some_xyz_users_alerts():
list_of_users = find_some_list_of_users()
for user in list_of_users:
send_user_alert.delay(user)
#celery.task(name='send_user_alert')
def send_user_alert(user):
data = get_data_for_user(user)
send_mail_to_user(data)
If we start send_some_xyz_users_alerts from our application it runs once. I then see 2 send_user_alert tasks running in celery for each user. Both these tasks have different task_ids. We have 2 workers running on server. Some times these duplicate tasks run on same worker. Sometimes on different workers. I have tried lot to find the problem without any luck. Would really appreciate if someone knows why this could happen. Things were running fine for months on these versions of celery and flask and suddenly we are seeing this problem on our servers. Tasks run fine on local env.
I am wondering what is the best way to decouple Celery from Django in order to dockerize the two parts and use docker swarm service? Typically one starts their celery workers and celery beat using a command that references there Django application:
celery worker -A my_app
celery beat -A my_app
From this I believe celery picks up config info from settings file and a celery.py file which is easy to move to a microservice. What I don't totally understand is how the tasks would leverage the Django ORM? Or is that not really the microservices mantra and Celery should be designed to make GET/POST calls to Django REST Framework API for the data it needs to complete the task?
I use a setup where the code for both the django app and its celery workers is the same (as in a single repository).
When deploying I make sure to have the same code release everywhere, to avoid any surprises with the ORM, etc...
Celery starts with a reference to the django app, so that it has access to the models, etc...
Communication between the workers and the main app happens either through the messaging queue (rabbitmq or redis...) or via the database (as in, the celery worker works directly in the db, since it knows the models, etc...).
I'm not sure if that follows the microservices mantra, but it does work :)
Celery's .send_task or .signature might be helpful:
https://www.distributedpython.com/2018/06/19/call-celery-task-outside-codebase/
I'm running a site using Django 10, RabbitMQ, and Celery 4 on CentOS 7.
My Celery Beat and Celery Worker instances are controlled by supervisor and I'm using the django celery database scheduler.
I've scheduled a cron style task using the cronsheduler in Django-admin.
When I start celery beat and worker instances the job fires as expected.
But if a change the schedule time in Django-admin then the changes are not picked up unless I restart the celery-beat instance.
Is there something I am missing or do I need to write my own scheduler?
Celery Beat, with the 'django_celery_beat.schedulers.DatabaseScheduler' loads the schedule from the database. According to the following doc https://media.readthedocs.org/pdf/django-celery-beat/latest/django-celery-beat.pdf this should force Celery Beat to reload:
A schedule that runs at a specific interval (e.g. every 5 seconds).
•
django_celery_beat.models.CrontabSchedule
A
schedule
with
fields
like
entries
in
cron: minute hour day-of-week day_of_month month_of_year.
django_celery_beat.models.PeriodicTasks
This model is only used as an index to keep track of when the schedule has changed. Whenever you update a PeriodicTask a counter in this table is also incremented, which tells the celery beat
service to reload the schedule from the database.
If you update periodic tasks in bulk, you will need to update the counter manually:
from django_celery_beat.models import PeriodicTasks
PeriodicTasks.changed()
From the above I would expect the Celery Beat process to check the table regularly for any changes.
i have changed the celery from 4.0 to 3.1.25, django to 1.9.11 and installed djcelery 3.1.17. Then test again, It's OK. So, maybe it's a bug.
I have a solution by:
Creating a separate worker process that consumes a RabbitMQ queue.
When Django updates the database it posts a message to the queue containing the name of the Celery Beat process (name defined by Supervisor configuration).
The worker process then restarts the named Celery Beat process.
A bit long winded but does the job. Also makes it easier to manage multiple Django apps on the same server that require the same functionality.
I have a celery instance running on heroku on a woker dyno. I use it with django and djcelery and I use the following command to start it:
python manage.py celery worker -B -E --loglevel=info --autoscale=50,8 --without-gossip
I added a task to the queue but it never got executed. The logs show this:
Scaling down -7 processes. (This is a while before the following)
Received task: myapp.tasks.my_task[75f095cb-9652-4cdb-87d4-dc31cecaadff]
Scaling up 1 processes.
But thats it, after this, the job didn't get done at all. I fired other tasks after this as well and all of them were successfully executed. The same issue was repeated a couple of hours later.
I have a few questions:
1. The "Received task ..." log line means that the celery daemon picked the job off of the queue, right? Why did the worker process become inactive?
2. Since my autoscale is set to 50,8, shouldn't there always be 8 workers? Why were all workers scaled down?
3. Is there any way to know that a task is stuck? What is the recommended failure recovery for such a case if the task being fired is mission critical.
My celery version is 3.1.9, django-celery version 3.1.9, redis version 2.6.16
Settings in django settings:
CELERY_SEND_TASK_ERROR_EMAILS = True
import djcelery
djcelery.setup_loader()
BROKER_URL = 'redis://:password#host:port/0'
BROKER_BACKEND = 'django'
CELERYBEAT_SCHEDULER = 'djcelery.schedulers.DatabaseScheduler'
I'm developing a web application with Django which uses Celery to process asynchronous tasks, especially for transactional emails.
One on my email task is scheduled with the ETA option but it's executed multiple times in parallel resulting in mail chain, very anoying. I can't figure out exactly why.
I checked twice my Django code and I'm sure that it is publish only one time.
I'm using Redis as a broker/backend result.
My Celery daemon is hosted on Heroku and launched via this command:
python manage.py celeryd -E -B --loglevel=INFO
Thanks for your help.
EDIT: I find a valid solution here thanks to a guy on the #celery IRC channel: http://loose-bits.com/2010/10/distributed-task-locking-in-celery.html
Have you checked the Ensuring a task is only executed one at a time docs?